如何根据其他事实从不同表中选择列以创建新的数据框python

Question

I have 2 DataFrames both countain countries 1-first have 183 row 2-the second have 156 row both of them has import information on each other I need one column from the first and one column from the second My goal is to create a single Dataframe contain both columns that I need and name of the contain that both datafames commo.

This is what I did and the message that I got

for i in range(183) :
    for j in range(156):
        if df['Country'][i]==df_happy['Country or region'][j]:
            df.drop(i,axis=0,inplace=True) 

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-25-e078ef71e219> in <module>
      1 for i in range(183) :
      2     for j in range(156):
----> 3         if df['Country'][i]==df_happy['Country or region'][j]:
      4             df.drop(i,axis=0,inplace=True)

/opt/conda/envs/Python-3.7-main/lib/python3.7/site-packages/pandas/core/series.py in __getitem__(self, key)
    869         key = com.apply_if_callable(key, self)
    870         try:
--> 871             result = self.index.get_value(self, key)
    872 
    873             if not is_scalar(result):

/opt/conda/envs/Python-3.7-main/lib/python3.7/site-packages/pandas/core/indexes/base.py in get_value(self, series, key)
   4403         k = self._convert_scalar_indexer(k, kind="getitem")
   4404         try:
-> 4405             return self._engine.get_value(s, k, tz=getattr(series.dtype, "tz", None))
   4406         except KeyError as e1:
   4407             if len(self) > 0 and (self.holds_integer() or self.is_boolean()):

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_value()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_value()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()

KeyError: 1

Answer 1

You can merge both data frames:

newdf=df.merge(df_happy,how='left', left_on='Country', right_on='Country or region')

and then drop the extra columns with:

newdf.drop(columns=['B', 'C'])